Enhanced p-sensitive k-anonymity models for privacy preserving data publishing

Sun, Xiaoxun and Wang, Hua and Li, Jiuyong and Truta, Traian Marius (2008) Enhanced p-sensitive k-anonymity models for privacy preserving data publishing. Transactions on Data Privacy, 1 (2). pp. 53-66. ISSN 1888-5063

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Publishing data for analysis from a micro data table containing sensitive attributes, while maintaining individual privacy, is a problem of increasing significance today. The k-anonymity model was proposed for privacy preserving data publication. While focusing on identity disclosure, k-anonymity model fails to protect attribute disclosure to some extent. Many efforts are made to enhance the k-anonymity model recently. In this paper, we propose two new privacy protectionmodels called (p, )-sensitive k-anonymity and (p+, )-sensitive k-anonymity, respectively. Different from previous the p-sensitive k-anonymity model, these new introduced models allow us to release a lot more information without compromising privacy. Moreover, we prove that the (p, )-sensitive and (p+, )-sensitive k-anonymity problems are NP-hard. We also include testing and heuristic generating algorithms to generate desired micro data table. Experimental results show that our introduced model could significantly reduce the privacy breach.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Authors retain copyright.
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 19 Oct 2009 23:35
Last Modified: 29 Aug 2014 05:00
Uncontrolled Keywords: k-anonymity models; privacy; data publishing
Fields of Research : 08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity
08 Information and Computing Sciences > 0804 Data Format > 080402 Data Encryption
08 Information and Computing Sciences > 0803 Computer Software > 080303 Computer System Security
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
URI: http://eprints.usq.edu.au/id/eprint/5907

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